方法证据记录
Generalized Additive Model
A generalized additive model, introduced by Trevor Hastie and Robert Tibshirani in 1986, extends the generalized linear model by replacing each linear term with a smooth, data-driven function of the predictor. This lets the model capture nonlinear relationships while preserving the additive, term-by-term interpretability of regression: each predictor contributes its own estimated curve, and the curves simply add up (on a link scale) to predict the response.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Generalized Additive Model (GAM)
分类方法记录 · ml-model / machine-learning
- Hastie, T., & Tibshirani, R. (1986). Generalized additive models. Statistical Science, 1(3), 297–310. · DOI 10.1214/ss/1177013604
- Hastie, T. J., & Tibshirani, R. J. (1990). Generalized Additive Models. Chapman & Hall/CRC. · ISBN 978-0-412-34390-2
精选声明
声明已持久化到证据分类账中,每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时,此视图不会自行创建声明评估。
相关方法
从方法图中生成,显示为机器建议的关系 — 不推断任何证据声明。